Journal of Computer Science

Text Summarization Using Morphological Filtering of Intuitionistic Fuzzy Hypergraph

Dhanya Prabhasadanam Mohanan, Sreekumar Ananda Rao, Jathavedan Madambi and Ramkumar Padinjarepizharath Balakrishna

DOI : 10.3844/jcssp.2018.837.853

Journal of Computer Science

Volume 14, Issue 6

Pages 837-853

Abstract

Text Summarization has been an area of interest for many years. It refers to creating a concise text of a document without any lose of information. Researchers in the area of natural language processing have developed many abstractive and extractive methods for creating summary. Abstractive summaries modifies the sentences and creates a modified concise form, while extractive summaries pick relevant sentences. The extractive method used in this study is a novel one which models the document as an Intuitionistic Fuzzy Hypergraph (IFHG). This IFHG is subjected to morphological filtering in order to create a concise summary. This is the premier work which applies morphological operations on IFHG that is modeled on a text. The method has generated summary which is almost similar to a human generated summary and showed more accuracy when compared with other machine generated summaries.

Copyright

© 2018 Dhanya Prabhasadanam Mohanan, Sreekumar Ananda Rao, Jathavedan Madambi and Ramkumar Padinjarepizharath Balakrishna. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.